The efficient use of memory is important in the design and operation of image processors. For example, consumer products such as television systems may use image processors including MPEG-2 signal processing. The MPEG (Motion Picture Experts Group) signal compression standard (ISO/IEC 13181-2, May 10, 1994) is a widely accepted image processing standard which is particularly attractive for use with satellite, cable and terrestrial broadcast systems employing high definition television (HDTV) processing among other forms of image processing. Products using high definition displays require 96 Mbits or more of memory to temporarily store MPEG decoded frames prior to display. An MPEG processor requires these frames for motion estimation and compensation to reconstruct accurate images for display.
Systems which reconstruct images from MPEG decoded picture elements (pixels or pels) employ Differential Pulse Coded Modulation (DPCM). In DPCM processing a processor generates a prediction value which anticipates the next pixel value. A summation network subtracts the prediction from the actual pixel value resulting in a difference which is used to represent the video data. This difference, known as prediction error, is generally smaller than the data value, so processing the difference rather than the original pixel value reduces system bandwidth requirements. The prediction error may have a positive or negative value. Ang et al., "Video Compression Makes Big Gains," IEEE Spectrum, October 1991, describes an MPEG encoder and decoder.
Memory efficient image processors use less memory to store image frames by recoding (recompressing) the block data prior to storage. In the spacial domain, reducing the number of bits per pixel used to store the image frames adversely affects the picture quality if the pixels can not be accurately reconstructed to their original value. Artifacts may occur, especially in smooth areas of the image. Memory reduction image processors should accurately quantize and dequantize the MPEG decoded signal as efficiently and economically as possible.
It is known to take advantage of human optical reception limitations and process luminance and chrominance data differently. Optimizing compression laws for each type of data to account for the energy and frequency components in the data, as well as what the human eye can see, is described in U.S. Pat. No. 4,575,749, by Acampora, et al. Acampora addresses amplitude compression to reduce noise in television signals prior to transmission. Display formats such as 4:2:2 and 4:2:0 also describe compression of video data where luminance and chrominance data have been processed differently. Format ratios 4:2:2 and 4:2:0 indicate that a chrominance data block contains one-half or one-quarter of the amount of information that a luminance data block contains. However, once the video data are received in a display processor, the data are represented as n-bit pixel data. The above known compression techniques do not address compression relative to the display processor.
In the display processor, luminance and chrominance data may be processed separately, but not with respect to recompression. An example of the display processor processing luminance and chrominance data differently would be converting 4:2:2 or 4:2:0 ratio data to raster line data, in that not every pixel is defined with chrominance information. However, this has nothing to do with compressing or recompressing data. Until the MPEG format became available, there was little concern for memory allocation for a display processor, because there was no need for calculating a picture frame from motion vectors or motion composition information. With the advent of the MPEG format, multiple frames of pixel data have to be stored in display associated memory to reconstruct picture frames. Co-pending application Ser. No. 08/579,129 describes recompression of video pixel data prior to storage in frame memory, before being received by the display processor.
More specifically, because chrominance data is commonly defined by fewer pixels (bit-limited) as compared to luminance data (e.g., in the 4:2:2 or 4:2:0 format), further compression or recompression of chrominance data is contraindicated. Compression or recompression of chrominance data, such as by means as quantization, now seriously compromises the ability to accurately reconstruct the original chrominance data for display resulting in reduced picture quality. Reducing memory requirements for display processors such as may be attained through recompressing luminance and chrominance pixel data prior to storage in frame memory, and the need for accurately reconstructing image data for display are competing interests relative to one another. This is particularly true in the case of a high definition system, such as HDTV, where details are clearly displayed.
The present inventors recognize the desirability of providing an efficient data reduction system employing minimal hardware and software which will save memory and reduce the physical size of the processor while minimizing artifacts introduced into the reconstructed image. The disclosed system solves these problems by processing luminance and chrominance data differently according to the principles of the present invention.